Validation of a Novel Intermittent W′ Model for Cycling Using Field Data

2014 ◽  
Vol 9 (6) ◽  
pp. 900-904 ◽  
Author(s):  
Philip F. Skiba ◽  
David Clarke ◽  
Anni Vanhatalo ◽  
Andrew M. Jones
Keyword(s):  
Roc Curve ◽  
Field Data ◽  
Critical Power ◽  
Intermittent Exercise ◽  
Work Capacity ◽  
Curve Analysis ◽  
Receiver Operator Characteristic ◽  
Roc Curve Analysis ◽  
New Development ◽  
The Mean

Recently, an adaptation to the critical-power (CP) model was published, which permits the calculation of the balance of the work capacity available above the CP remaining (W′bal) at any time during intermittent exercise. As the model is now in use in both amateur and elite sport, the purpose of this investigation was to assess the validity of theW′balmodel in the field. Data were collected from the bicycle power meters of 8 trained triathletes.W′balwas calculated and compared between files where subjects reported becoming prematurely exhausted during training or competition and files where the athletes successfully completed a difficult assigned task or race without becoming exhausted. CalculatedW′balwas significantly different between the 2 conditions (P< .0001). The meanW′balat exhaustion was 0.5 ± 1.3 kJ (95% CI = 0–0.9 kJ), whereas the minimumW′balin the nonexhausted condition was 3.6 ± 2.0 kJ (95% CI = 2.1–4.0 kJ). Receiver-operator-characteristic (ROC) curve analysis indicated that theW′balmodel is useful for identifying the point at which athletes are in danger of becoming exhausted (area under the ROC curve = .914, SE .05, 95% CI .82–1.0,P< .0001). TheW′balmodel may therefore represent a useful new development in assessing athlete fatigue state during training and racing.

scholarly journals CLINICAL SIGNIFICANCE OF PROCALCITONIN AND C-REACTIVE PROTEIN IN THE PREDICTION OF CARDIOVASCULAR COMPLICATIONS IN PATIENTS WITH TYPE 2 DIABETES MELLITUS

2017 ◽  
Vol 10 (9) ◽  
pp. 297
Author(s):  
Hanaa H. Ahmed ◽  
Wafaa Gh Shousha ◽  
Hatem A El Mezayen ◽  
Ibrahim A Emara ◽  
Marwa E Hassan
Keyword(s):  
Roc Curve ◽  
Cardiovascular Complication ◽  
Curve Analysis ◽  
Diabetic Patients ◽  
C Reactive Protein ◽  
Roc Curve Analysis ◽  
Reactive Protein ◽  
The Mean ◽  
Type 2 Diabetic

  Objective: This work was delineated to assess procalcitonin (PCT) and C-reactive protein (CRP) as prognostic markers for cardiovascular complication in type 2 diabetic patients.Methods: Forty diabetic patients without cardiovascular disease (CVD), 40 diabetic patients with CVD, and 20 healthy control counterparts were participated in this study. Serum PCT and CRP levels were assayed and correlated with metabolic parameters. Receiver operating characteristic (ROC) curve analysis was done for each biochemical marker.Results: The mean level of PCT was 707.17±99.19 ng/l in diabetic patients versus 881.30±123.56 ng/l for the cardio-diabetic patients (p<0.0001). The mean value of CRP was 34.43±17.27 mg/l in diabetic patients versus 50.32±20.19 mg/l for the cardio-diabetic patients (p=0.0003). PCT levels were significantly amplified in the cardio-diabetic patients with increasing CRP, triglycerides (TG), fasting blood glucose (FBG), and cholesterol (p=0.004, 0.0005, 0.002, and 0.01, respectively). CRP levels were significantly enhanced in the cardio-diabetic patients with increasing TG, FBG, cholesterol, and microalbumin (p=0.002, 0.047, 0.003, and 0.001 respectively). ROC curve analysis for PCT and CRP revealed that the area under curve (AUC) was 0.878 and 0.727, respectively. These findings indicate the good validity of the above biomarkers especially PCT as a prognostic marker for cardiovascular complication in type 2 diabetic patients.Conclusion: This study evidences the usefulness of measuring serum levels of PCT and CRP in diagnosis of cardiovascular complication in type 2 diabetic patients.

Screening for cognitive deficits with the Evaluation of Cognitive Processes involved in Disability in Schizophrenia scale

2018 ◽  
Vol 33 (1) ◽  
pp. 113-119 ◽  
Author(s):  
Paul Roux ◽  
Mathieu Urbach ◽  
Sandrine Fonteneau ◽  
Fabrice Berna ◽  
Lore Brunel ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Cognitive Processes ◽  
Roc Curve ◽  
Standardized Test ◽  
Curve Analysis ◽  
Index Test ◽  
Neuropsychological Battery ◽  
Roc Curve Analysis ◽  
Cognitive Domains ◽  
The Mean

Objective: This study aimed to evaluate the validity of the Evaluation of Cognitive Processes involved in Disability in Schizophrenia scale (ECPDS) to discriminate for cognitive impairment in schizophrenia. Design: This multicentre cross-sectional study used a validation design with receiver operating characteristic (ROC) curve analysis. Settings: The study was undertaken in a French network of seven outward referral centres. Subjects: We recruited individuals with clinically stable schizophrenia diagnosed based on the Structured Clinical Interview for assessing Diagnostic and Statistical Manual of Mental Disorders (4th ed., rev.; DSM-IV-R) criteria. Main measures: The index test for cognitive impairment was ECPDS (independent variable), a 13-item scale completed by a relative of the participant. The reference standard was a standardized test battery that evaluated seven cognitive domains. Cognitive impairment was the dependent variable and was defined as an average z-score more than 1 SD below the normative mean in two or more cognitive domains. Results: Overall, 97 patients were included (67 with schizophrenia, 28 with schizoaffective disorder, and 2 with schizophreniform disorder). The mean age was 30.2 (SD 7.7) years, and there were 75 men (77.3%). There were 59 (60.8%) patients with cognitive impairment on the neuropsychological battery, and the mean ECPDS score was 27.3 (SD 7.3). The ROC curve analysis showed that the optimal ECPDS cut-off was 29.5. The area under the curve was 0.77, with 76.3% specificity and 71.1% sensitivity to discriminate against cognitive impairment. Conclusion: The ECPDS is a valid triage tool for detecting cognitive impairment in schizophrenia, before using an extensive neuropsychological battery, and holds promise for use in everyday clinical practice.

scholarly journals Lung ultrasound in patients with rheumatoid arthritis and the definition of significant interstitial lung disease

2020 ◽  
Author(s):  
Marco Di Carlo ◽  
Marika Tardella ◽  
Emilio Filippucci ◽  
Marina Carotti ◽  
Fausto Salaffi
Keyword(s):  
Rheumatoid Arthritis ◽  
Interstitial Lung Disease ◽  
Lung Disease ◽  
Roc Curve ◽  
Lung Ultrasound ◽  
Smoking Habit ◽  
Curve Analysis ◽  
Roc Curve Analysis ◽  
The Mean ◽  
B Lines

Abstract Background. In recent years, a growing interest has grown around interstitial lung disease (ILD) in patients with rheumatoid arthritis (RA). While high resolution computed tomography (HRCT) of the chest remains the diagnostic method of choice, increasing attention has been directed towards lung ultrasound (LUS) in the diagnosis of ILD in connective tissue diseases. However, in patients with RA it is not yet clear how to interpret, in quantitative terms, the presence of B-lines, the LUS artifact indicative of ILD. The aim of this study was to determine the cut-off number of LUS B-lines that identifies a significant RA-ILD.Methods. A cross sectional study was conducted on consecutive RA patients with suspected RA-ILD. The inclusion criteria were clinical (dyspnea, velcro sounds), instrumental (suggestive anomalies on conventional radiography, DLco reduction), or in presence of at least two of the following risk factors for RA-ILD: smoking habit, male sex, advanced age, and ACPA presence.Patients underwent LUS (carried out in 14 defined intercostal spaces), chest HRCT, pulmonary function tests, and clinical evaluation. The diagnosis of RA-ILD was based on a semi-quantitative evaluation of chest HRCT using a computer-aided method (CaM). The discriminative validity of the LUS versus HRCT has been studied by using the receiver operating characteristic (ROC) curve analysis.Results. 72 consecutive RA patients (21 male, 51 female) were evaluated, with a mean age of 63.0 (SD 11.5 years). The mean estimate of pulmonary fibrosis using the CaM was 11.20% (SD 7.48) at chest HRCT, while at LUS the mean number of B-lines was 10.65 (SD 15.11). A significant RA-ILD, as measured by the CaM at HRCT, was detected in 25 patients (34.7%). The presence of 9 B-lines was found to be the optimal cut-off at ROC curve analysis. This LUS cut-off defines the presence of significant RA-ILD with a sensitivity of 70.0%, a specificity of 97.62%, and a positive likelihood ratio of 29.4.Conclusion. The present study provided data to determine the number of B-lines to identify a significant RA-ILD. LUS may represent a useful technique to select RA patients to be assessed by chest HRCT.

scholarly journals The Value of Magnetic Resonance Imaging Histograms in the Preoperative Differential Diagnosis of Endometrial Stromal Sarcoma and Degenerative Hysteromyoma

2021 ◽  
Vol 8 ◽  
Author(s):  
Xiao-Nan Zhang ◽  
Man Bai ◽  
Ke-Ran Ma ◽  
Yong Zhang ◽  
Cheng-Ru Song ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Differential Diagnosis ◽  
Roc Curve ◽  
Endometrial Stromal Sarcoma ◽  
Curve Analysis ◽  
Resonance Imaging ◽  
Roc Curve Analysis ◽  
Diagnostic Efficacy ◽  
Stromal Sarcoma ◽  
The Mean

Objective: The present study aimed to explore the application value of magnetic resonance imaging (MRI) histograms with multiple sequences in the preoperative differential diagnosis of endometrial stromal sarcoma (ESS) and degenerative hysteromyoma (DH).Methods: The clinical and preoperative MRI data of 20 patients with pathologically confirmed ESS and 24 patients with pathologically confirmed DH were retrospectively analyzed, forming the two study groups. Mazda software was used to select the MRI layer with the largest tumor diameter in T2WI, the apparent diffusion coefficient (ADC), and enhanced T1WI (T1CE) images. The region of interest (ROI) was outlined for gray-scale histogram analysis. Nine parameters—the mean, variance, kurtosis, skewness, 1st percentile, 10th percentile, 50th percentile, 90th percentile, and 99th percentile—were obtained for intergroup analysis, and the receiver operating curves (ROCs) were plotted to analyze the differential diagnostic efficacy for each parameter.Results: In the T2WI histogram, the differences between the two groups in seven of the parameters (mean, skewness, 1st percentile, 10th percentile, 50th percentile, 90th percentile, and 99th percentile) were statistically significant (P &lt; 0.05). In the ADC histogram, the differences between the two groups in three of the parameters (skewness, 10th percentile, and 50th percentile) were statistically significant (P &lt; 0.05). In the T1CE histogram, no significant differences were found between the two groups in any of the parameters (all P &gt; 0.05). Of the nine parameters, the 50th percentile was found to have the best diagnostic efficacy. In the T2WI histogram, ROC curve analysis of the 50th percentile yielded the best area under the ROC curve (AUC; 0.742), sensitivity of 70%, and specificity of 83.3%. In the ADC histogram, ROC curve analysis of the 50th percentile yielded the best area under the ROC curve (AUC; 0.783), sensitivity of 81%, and specificity of 76.9%.Conclusion: The parameters of the mean, 10th percentile and 50th percentile in the T2WI histogram have good diagnostic efficacy, providing new methods and ideas for clinical diagnosis.

scholarly journals Lung ultrasound in patients with rheumatoid arthritis and the definition of significant interstitial lung disease

2020 ◽  
Author(s):  
Marco Di Carlo ◽  
Marika Tardella ◽  
Emilio Filippucci ◽  
Marina Carotti ◽  
Fausto Salaffi
Keyword(s):  
Rheumatoid Arthritis ◽  
Interstitial Lung Disease ◽  
Lung Disease ◽  
Roc Curve ◽  
Lung Ultrasound ◽  
Smoking Habit ◽  
Curve Analysis ◽  
Roc Curve Analysis ◽  
The Mean ◽  
B Lines

Abstract Background In recent years, a growing interest has grown around interstitial lung disease (ILD) in patients with rheumatoid arthritis (RA). While high resolution computed tomography (HRCT) of the chest remains the diagnostic method of choice, increasing attention has been directed towards lung ultrasound (LUS) in the diagnosis of ILD in connective tissue diseases. However, it is not yet well defined how to interpret the LUS findings under suspicion of RA-ILD. The aim of this study was to determine the cut-off number of LUS B-lines that identifies a significant RA-ILD. Methods A cross sectional study was conducted on consecutive RA patients with suspected RA-ILD. The inclusion criteria were clinical (dyspnea, velcro sounds), instrumental (suggestive anomalies on conventional radiography, DLco reduction), or in presence of at least two of the following risk factors for RA-ILD: smoking habit, male sex, advanced age, and ACPA presence. Patients underwent LUS (carried out in 14 defined intercostal spaces), chest HRCT, pulmonary function tests, and clinical evaluation. The diagnosis of RA-ILD was based on a semi-quantitative evaluation of chest HRCT using a computer-aided method (CaM). The discriminative validity of the LUS versus HRCT has been studied by using the receiver operating characteristic (ROC) curve analysis. Results 72 consecutive RA patients (21 male, 51 female) were evaluated, with a mean age of 63.0 (SD 11.5 years). The mean estimate of pulmonary fibrosis using the CaM was 11.20% (SD 7.48) at chest HRCT, while at LUS the mean number of B-lines was 10.65 (SD 15.11). A significant RA-ILD, as measured by the CaM at HRCT, was detected in 25 patients (34.7%). The presence of 9 B-lines was found to be the optimal cut-off at ROC curve analysis. This LUS cut-off defines the presence of significant RA-ILD with a sensitivity of 70.0%, a specificity of 97.62%, and a positive likelihood ratio of 29.4. Conclusion The present study provided data to determine the number of B-lines to identify a significant RA-ILD. LUS may represent a useful technique to select RA patients to be assessed by chest HRCT.

Side Scatter Level of Main Populations in Peripheral Blood using Flow Cytometry as a Tool for the Screening/Detection of Dysplasia and Its Utility in the Diagnosis of Myelodysplastic Syndromes

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 5091-5091
Author(s):  
Ekaterina Rusanova ◽  
Ramon Simon-Lopez
Keyword(s):  
Flow Cytometry ◽  
Myelodysplastic Syndromes ◽  
Roc Curve ◽  
Statistical Significance ◽  
Area Under The Curve ◽  
Curve Analysis ◽  
Control Group ◽  
Roc Curve Analysis ◽  
Significance Level ◽  
The Mean

Abstract The myelodysplastic syndromes (MDS) are a group of clonal bone marrow disorders characterized by peripheral cytopenias, ineffective hematopoiesis, and unilineage or multilineage dysplasia. The feature used commonly for the diagnostic of MDS includes several morphological cell characteristics such as the presence of hypogranulation in the neutrophils. We have observed in our daily experience at the Mean Scatter of neutrophils was lower in MDS than in normal cases. We have observed that Lymphocyte scatter is quite constant in normal cases and in the majority of MDS. 11 patients diagnosed with MDS and 16 normal blood donors as a control group were enrolled into this study. The protocol of study included evaluation of blood cell populations by hematological analyzer GenS (BC), smears microscopy and flow cytometry for identification a level of granularity of neutrophils (FC500, BC). We created a single tube protocol for immunophenotyping of blood cells by multiparametric flow cytometry using a panel of monoclonal antibodies: CD14-FITC, CD16-PE, CD33-PC5 and CD45-PC7 (BC). We isolated the neutrophil and the lymphocyte populations by subsequent gating steps according to FS/SS, CD45/SS, CD45/CD16 and CD33/CD14. After gating, we measured the Mean Side Scatter in lymphocytes and neutrophils. In order to standardize the NE Mean Scatter we used also a ratio that was calculated by dividing the Neutrophil Mean Scatter by Lymphocyte Mean Scatter. Descriptive Statistics Mean Scatter n Mean SD Median Normals 16 633.6 99.7 612 MDS 11 564.4 83.1 543 Comparative Statistics Normals vs MDS T-test Mean differences ROC AUC ROC cut-off sensitivity specificity sign. ROC Mean NE Scatter 0.071 69.11 0.685 &lt;=543 54.5 87.5 0.0732 Ratio NES/LYS 0.016 2.175 0.824 &lt;=8.34 81.82 81.25 0.0001 The results show the consistent differences between the Neutrophil Mean Scatter in the MDS group compared with the normals with a p =0.07 near the level of statistical significance. The Ratio between Mean Scatter of Neutrophils and the Mean Scatter of Lymphocytes (Ratio NE S/LY S) was significantly lower in MDS than in the group of normals (p=0.016). The ROC Curve analysis using the Neutrophil Mean Scatter to detect/flag MDS showed an acceptable area under the curve AUC=0.685 (significance level 0.073) with a cut-off of &lt;=533 we obtain a sensitivity of 54.5% with a specificity of 87.5%. The ROC Curve analysis using the Ratio NE S/LY S to detect/flag MDS have shown a good area under the curve AUC=0.824 (significance level 0.0001) with a cut-off of &lt;=8.34 we obtain a sensitivity of 81.8% with a specificity of 81.2%. The fact about hypogranularity of the neutrophils is a well known feature of MDS. Using the Neutrophil Mean Scatter and the Ratio between Mean Scatter of Neutrophils and the Mean Scatter of Lymphocytes may be useful tool to detect or flag the neutrophil hypogranularity and will permit to help in the differential diagnosis of MDS. These data are numerical, quantitative and objective. It will be necessary to increase the number of cases (MDS) and to include other hematologic malignancies in order to see the specificity of this findings compared with other diseases.

The Comparison of Platelet Parameters in Patients with Thrombocytopenia Associated with Acute Myeloid Leukemia and Immune Thrombocytopenia

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 3317-3317
Author(s):  
Moon-Jin Kim ◽  
Jeong-Yeal Ahn ◽  
Pil-Whan Park ◽  
Yiel-Hea Seo ◽  
Kyung-Hee Kim ◽  
...  
Keyword(s):  
Roc Curve ◽  
Myeloid Leukemia ◽  
Immune Thrombocytopenia ◽  
Reference Range ◽  
Curve Analysis ◽  
Roc Curve Analysis ◽  
Mean Values ◽  
Platelet Production ◽  
The Mean ◽  
Acute Myeloid

Abstract Abstract 3317 Parameters associated with platelets (PLT) other than total PLT count, mean platelet volume (MPV), and platelet distribution width (PDW) are not widely used in clinical fields, although recent researches about them are increasingly reported. Additional platelet parameters can be helpful to evaluate the underlying cause of thrombocytopenia induced by two mechanisms-insufficient production and destruction of platelets. We investigated the significance of platelet parameters by evaluation of patients with ineffective platelet production (acute myeloid leukemia, AML) and destruction of platelets (immune thrombocytopenia, ITP). 49 adults newly diagnosed with AML (median age: 60, range: 21–86 years old) who had thrombocytopenia (<150 ×103/uL) and 47 adults with ITP (median age: 44, range: 22–82 years old) who were diagnosed with the bone marrow (BM) study were retrospectively reviewed. PLT and PLT parameters - MPV, PDW, PLT crit (PCT), mean PLT component (MPC), mean PLT mass (MPM), and large PLT count (LPLT) were measured by the ADVIA 2120 Hematology System (Siemens, USA) at the time of diagnosis. The percentage of LPLT (LPLT%) was calculated (LPLT/PLT ×100). The mean values of each group were compared using independent T-test on SPSS. The sensitivity and the specificity of each item to differentiate AML and ITP were determined by receiver operating characteristic (ROC) curve analysis. The mean values of platelet parameters of 480 male and female Korean adults in different age groups (120 in each group) who had hemoglobin level of 12–16.5 g/dl in female and 13–18.5 g/dl in male, white blood cell count of 4–10 ×103/ul, and PLT of 150–450 ×103/ul are shown in table I. The mean values of MPV, PDW, MPC, MPM, and LPLT% of ITP patients were significantly higher than those of AML (p<0.05). PLT, PCT, and LPLT did not show the difference between AML and ITP patients (Table II). Also, MPV, PDW, MPC, MPM, and LPLT% appeared significant to differentiate two diseases (p<0.05) upon ROC curve analysis (Table III). Table I. Platelet parameters in 480 Korean adults Platelet parameters Mean ¡¾ SD Total Male under 50Y Male over 50Y Female under 50Y Female over 50Y Reference range PLT (×103/¥ìl) 261 ¡¾ 53 257 ¡¾ 52 241 ¡¾ 47 259 ¡¾ 51 280 ¡¾ 59 150–450 MPV (fl) 7.9 ¡¾ 1.0 7.7 ¡¾ 0.7 7.9 ¡¾ 0.7 7.9 ¡¾ 0.7 8.0 ¡¾ 1.8 9–13 PDW (%) 51.3 ¡¾ 7.5 51.6 ¡¾ 7.5 52.1 ¡¾ 7.1 52.2 ¡¾ 5.8 49.0 ¡¾ 9.0 N PCT (%) 0.20 ¡¾ 0.04 0.20 ¡¾ 0.04 0.19 ¡¾ 0.04 0.20 ¡¾ 0.06 0.20 ¡¾ 0.04 N MPC (g/dl) 26.0 ¡¾ 1.3 26.2 ¡¾ 1.4 25.8 ¡¾ 1.3 26.4 ¡¾ 1.0 25.5 ¡¾ 1.5 N MPM (pg) 1.9 ¡¾ 0.2 1.9 ¡¾ 0.2 1.9 ¡¾ 0.2 2.0 ¡¾ 0.2 1.9 ¡¾ 0.2 N LPLT (×103/¥ìl) 4.7 ¡¾ 2.7 4.5 ¡¾ 2.7 4.6 ¡¾ 3.1 4.9 ¡¾ 2.3 4.7 ¡¾ 2.8 N LPLT% (%) 1.7 ¡¾ 0.6 1.8 ¡¾ 1.3 2.0 ¡¾ 1.4 2.0 ¡¾ 1.1 1.8 ¡¾ 1.2 N Abbreviations: SD, Standard deviation; Y, years old; N, Not determined; see text. Table II. Platelet parameters in AML and ITP patients Platelet parameters Disease Mean ¡¾ SD Reference range PLT (×103/¥ìl) AML 59 ¡¾ 35 150-450 ITP 54 ¡¾ 29 MPV* (fl) AML 9.8 ¡¾ 2.1 9–13 ITP 10.9 ¡¾ 2.8 PDW* (%) AML 53.9 ¡¾ 17.0 N ITP 60.6 ¡¾ 12.1 PCT (%) AML 0.06 ¡¾ 0.04 N ITP 0.06 ¡¾ 0.03 MPC* (g/dl) AML 22.3 ¡¾ 2.1 N ITP 25.4 ¡¾ 2.2 MPM* (pg) AML 2.0 ¡¾ 0.3 N ITP 2.4 ¡¾ 0.4 LPLT (×103/¥ìl) AML 3 ¡¾ 5 N ITP 4 ¡¾ 6 LPLT%* (%) AML 4.7 ¡¾ 5.2 N ITP 8.3 ¡¾ 9.4 Abbreviations: See table I; see text. * p<0.05. Table III. AUC for differentiation of AML and ITP with cut-off values ¡¡ AUC (95% CI) Cut-off value Sensitivity (%) Specificity (%) PLT 0.48 (0.36–0.59) 68 ×103/¥ìL 34.0 74.6 MPV* 0.66 (0.55–0.77) 10.2 fL 57.4 78.0 PDW* 0.63 (0.53–0.74) 56.3 % 66.0 69.5 PCT 0.51 (0.40–0.62) 0.07 % 40.4 72.9 MPC* 0.84 (0.78–0.92) 2.1 g/dL 87.2 76.3 MPM* 0.85 (0.75–0.91) 22.5 pg 78.7 76.3 LPLT 0.61 (0.50–0.71) 5.5 ×103/¥ìL 21.3 89.8 LPLT%* 0.67 (0.57–0.77) 4.1 % 72.3 61.0 Abbreviations: AUC, areas under the curves; CI, confidence interval; see text. * : p<0.05. In AML, deficient platelet production in the BM causes thrombocytopenia. Immune mediated destruction in the peripheral blood induces thrombocytopenia in ITP in spite of activated PLT production in BM. MPV, PDW and platelet large cell ratio (P-LCR measured by Sysmex-XE2100) had been reported to reflect production rate (MPV and PDW) and percentage of immature platelets (P-LCR) so that being higher in ITP than aplastic anemia (Kaito et al, 2004). MPV, PDW, MPC, MPM, and LPLT% were higher in ITP than AML in our study. They are also proven to differentiate AML and ITP upon ROC curve analysis. MPV, PDW, and LPLT% can be used as markers to predict the status of thrombopoiesis differentiating two mechanisms of thrombocytopenia, deficiency of production and destruction of platelets. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Modified zwolle score with delta-creatinine: enhancing the safety of early discharge after STEMI

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
D Bras ◽  
J Pais ◽  
M Carrington ◽  
A.R Rocha ◽  
B Picarra ◽  
...  
Keyword(s):  
Roc Curve ◽  
Roc Curves ◽  
Early Discharge ◽  
Early Mortality ◽  
Curve Analysis ◽  
Low Risk ◽  
Roc Curve Analysis ◽  
C Statistic ◽  
Risk Patients ◽  
The Mean

Abstract Introduction The Zwolle score (ZS) is recommended to identify low-risk patients eligible for early discharge after acute ST-segment elevation myocardial infarction (STEMI), but as only one-third of STEMIs have a low ZS, the discharge is often postponed. Creatinine variation (Δ-Cr) also provide prognostic information after STEMI. Purpose The authors intend to study the “modified Zwolle Score” (MZS) model, which encompasses Δ-Cr as a variable that may enhance the discriminative power of the standard ZS. The outcome is 30-day mortality, time range that starts right after the ACS. Methods This is a retrospective study with data from a national multicentre registry. We have included 3.296 patients with STEMI. Zwolle score was calculated for each patient. It is defined as shown in figure 1. Δ-Cr was defined as maximum serum creatinine minus admission serum creatinine. A Δ-Cr≥0.3 was assigned 2 points in the Modified Zwolle Score, after interpretation of odds ratio via multivariate analysis. For prediction quality assessment, we have performed ROC curve analysis with both scoring systems versus 30-day mortality. Regarding survival analysis, we have performed Kaplan-Meier curves with Log-rank analysis. We have also registered complications during hospital stay. Results The sample mean age is 63±14, and it is composed by 76.8% of males. The majority of patients presented Killip Class I (87.3%). The STEMI was anterior in 49.7% of patients and inferior in 49.8% of patients. The mean admission time was 5 days. Intrahospital mortality was 3% and 30-day mortality was 4%. The mean ZS was 3.1±2.8 points, the mean MZS was 3±2.1 points and the mean Δ-Cr was 0.2±0.6mg/dL. The ROC curve analysis between ZS and early mortality revealed a c-statistic of 0.810 (CI 0.796–0.823), whereas the ROC curve between MZS and early mortality revealed a c-statistic of 0.853 (95% CI: 0.841–0.865). The ROC curves comparison showed superiority of the MZS c-statistic, with a difference between AUC of 0.043 (p&lt;0.001, 95% CI: 0.024–0.063). Regarding low-risk patients, 30-day mortality was 3.3% using ZS (0–2 points) and 2.4% using modified ZS (0–2 points). Fifty patients (1.5%) died between 3rd and 10th day after ACS: original ZS low-risk criteria registered 0.09% and modified ZS low-risk criteria 0.06% fatalities. Kappa coefficient for intergroup concordance was good (0.73). Conclusion We conclude that by adding Δ-Cr to the standard ZS, a renal function parameter that was lacking in the ZS, its predicting capacity regarding early mortality in patients admitted with STEMI was increased. Comparing both scores, low-risk patients defined by MZS registered less complications, 3–10 day mortality and 30-day mortality than low-risk patients defined by the original ZS. This fact may lead to better distinction of patients who will benefit from early discharge. Zwolle Score, ROC curves and survival Funding Acknowledgement Type of funding source: None

Acute heart failure: predicting early in-hospital outcomes

2021 ◽  
Vol 28 (Supplement_1) ◽  
Author(s):  
M Santos ◽  
S Paula ◽  
I Almeida ◽  
H Santos ◽  
H Miranda ◽  
...  
Keyword(s):  
Heart Failure ◽  
Logistic Regression ◽  
Acute Heart Failure ◽  
Roc Curve ◽  
Real Life ◽  
Study Data ◽  
Curve Analysis ◽  
Older Age ◽  
Invasive Ventilation ◽  
Roc Curve Analysis

Abstract Funding Acknowledgements Type of funding sources: None. Introduction Patients (P) with acute heart failure (AHF) are a heterogeneous population. Risk stratification at admission may help predict in-hospital complications and needs. The Get With The Guidelines Heart Failure score (GWTG-HF) predicts in-hospital mortality (M) of P admitted with AHF. ACTION ICU score is validated to estimate the risk of complications requiring ICU care in non-ST elevation acute coronary syndromes. Objective To validate ACTION-ICU score in AHF and to compare ACTION-ICU to GWTG-HF as predictors of in-hospital M (IHM), early M [1-month mortality (1mM)] and 1-month readmission (1mRA), using real-life data. Methods Based on a single-center retrospective study, data collected from P admitted in the Cardiology department with AHF between 2010 and 2017. P without data on previous cardiovascular history or uncompleted clinical data were excluded. Statistical analysis used chi-square, non-parametric tests, logistic regression analysis and ROC curve analysis. Results Among the 300 P admitted with AHF included, mean age was 67.4 ± 12.6 years old and 72.7% were male. Systolic blood pressure (SBP) was 131.2 ± 37.0mmHg, glomerular filtration rate (GFR) was 57.1 ± 23.5ml/min. 35.3% were admitted in Killip-Kimball class (KKC) 4. ACTION-ICU score was 10.4 ± 2.3 and GWTG-HF was 41.7 ± 9.6. Inotropes’ usage was necessary in 32.7% of the P, 11.3% of the P needed non-invasive ventilation (NIV), 8% needed invasive ventilation (IV). IHM rate was 5% and 1mM was 8%. 6.3% of the P were readmitted 1 month after discharge. Older age (p &lt; 0.001), lower SBP (p = 0,035) and need of inotropes (p &lt; 0.001) were predictors of IHM in our population. As expected, patients presenting in KKC 4 had higher IHM (OR 8.13, p &lt; 0.001). Older age (OR 1.06, p = 0.002, CI 1.02-1.10), lower SBP (OR 1.01, p = 0.05, CI 1.00-1.02) and lower left ventricle ejection fraction (LVEF) (OR 1.06, p &lt; 0.001, CI 1.03-1.09) were predictors of need of NIV. None of the variables were predictive of IV. LVEF (OR 0.924, p &lt; 0.001, CI 0.899-0.949), lower SBP (OR 0.80, p &lt; 0.001, CI 0.971-0.988), higher urea (OR 1.01, p &lt; 0.001, CI 1.005-1.018) and lower sodium (OR 0.92, p = 0.002, CI 0.873-0.971) were predictors of inotropes’ usage. Logistic regression showed that GWTG-HF predicted IHM (OR 1.12, p &lt; 0.001, CI 1.05-1.19), 1mM (OR 1.10, p = 1.10, CI 1.04-1.16) and inotropes’s usage (OR 1.06, p &lt; 0.001, CI 1.03-1.10), however it was not predictive of 1mRA, need of IV or NIV. Similarly, ACTION-ICU predicted IHM (OR 1.51, p = 0.02, CI 1.158-1.977), 1mM (OR 1.45, p = 0.002, CI 1.15-1.81) and inotropes’ usage (OR 1.22, p = 0.002, CI 1.08-1.39), but not 1mRA, the need of IV or NIV. ROC curve analysis revealed that GWTG-HF score performed better than ACTION-ICU regarding IHM (AUC 0.774, CI 0.46-0-90 vs AUC 0.731, CI 0.59-0.88) and 1mM (AUC 0.727, CI 0.60-0.85 vs AUC 0.707, CI 0.58-0.84). Conclusion In our population, both scores were able to predict IHM, 1mM and inotropes’s usage.

scholarly journals Presepsin values and prognostic nutritional index predict mortality in intensive care unit patients with sepsis: a pilot study

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Yuichiro Shimoyama ◽  
Osamu Umegaki ◽  
Noriko Kadono ◽  
Toshiaki Minami
Keyword(s):  
Multivariate Analysis ◽  
Roc Curve ◽  
Operating Characteristic ◽  
Prognostic Nutritional Index ◽  
Early Mortality ◽  
Curve Analysis ◽  
Rank Test ◽  
Roc Curve Analysis ◽  
Log Rank Test ◽  
Nutritional Index

Abstract Objective Sepsis is a major cause of mortality for critically ill patients. This study aimed to determine whether presepsin values can predict mortality in patients with sepsis. Results Receiver operating characteristic (ROC) curve analysis, Log-rank test, and multivariate analysis identified presepsin values and Prognostic Nutritional Index as predictors of mortality in sepsis patients. Presepsin value on Day 1 was a predictor of early mortality, i.e., death within 7 days of ICU admission; ROC curve analysis revealed an AUC of 0.84, sensitivity of 89%, and specificity of 77%; and multivariate analysis showed an OR of 1.0007, with a 95%CI of 1.0001–1.0013 (p = 0.0320).

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